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An Approach to Identify Bottlenecks in Road Networks using Travel Time Variations: A Case Study in the City of Colombo and Suburbs

机译:一种基于行驶时间变化来识别道路网瓶颈的方法:以科伦坡和郊区城市为例

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Bottlenecks in road networks are the main contributing factor in terms of traffic congestion in urban areas and thus, identification of bottlenecks and introduction of relevant remedies are important in easing the traffic congestion especially in the case of developing countries where funding for new transport infrastructure projects is a major factor of concern. This study discusses on identification of bottlenecks using crowdsource real- time travel time data which is more effective in terms of collection and usage in analysis. The usual travel time collection process is thus replaced by using Google Maps API matrix. Shortest travel time and travel distance paths among main origin and destinations are analyzed and the contrast in shortest distance path not being the shortest travel time path brings an important consideration of the reasons associated mainly due to presence of bottlenecks which needs to be identified and rectified for better road user experience. After a macro level approach in the identification process, certain transportation indices such as Congestion Index, Delay Rate Index and Travel Rate Ratio in a meso and micro level analysis perspective are utilized to ensure the identification of critical bottlenecks along minimum distance paths in the road network of main roads.
机译:道路网络的瓶颈是造成城市地区交通拥堵的主要因素,因此,确定瓶颈和采取相关的补救措施对于缓解交通拥堵至关重要,特别是在发展中国家,在这些国家中,为新的交通基础设施项目提供了资金。一个值得关注的主要因素。本研究讨论了使用众包实时旅行时间数据来识别瓶颈,这在收集和使用分析方面更为有效。因此,使用Google Maps API矩阵取代了通常的旅行时间收集过程。分析了主要起点和目的地之间的最短旅行时间和旅行距离路径,并且最短距离路径(不是最短旅行时间路径)中的对比度带来了重要的考虑因素,主要是由于存在瓶颈而需要对此进行识别和纠正的相关原因更好的道路用户体验。在识别过程中采用宏观方法之后,利用中观和微观分析角度的某些运输指标(例如拥堵指数,延迟率指数和行驶率比)来确保识别沿道路网最小距离路径的关键瓶颈主要道路。

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